ISO-NE PUBLIC Al McBride, Fei Zeng SYSTEM PLANNING Forward Capacity Market Zonal Demand Curves JANUARY 20, 2016 | MILFORD, MA Reliability Committee
ISO-NE PUBLIC
Al McBride, Fei Zeng S Y S T E M P L A N N I N G
Forward Capacity Market Zonal Demand Curves
J A N U A R Y 2 0 , 2 0 1 6 | M I L F O R D , M A
Reliability Committee
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FCM Zonal Demand Curves
Proposed Effective Date: FCA 11
• ISO is proposing new zonal demand curves for the FCA – Improve locational price signals in the FCM – Better reflect incremental reliability impact of capacity than existing
(fixed) zonal requirements – Derived using a methodology that satisfies three core design principles – Robust to zonal configuration changes – Comply with FERC Order requiring zonal curves for FCA 11
• This meeting: – Discuss stakeholder and filing schedule in light of Dec. 28 FERC Order – Explain zonal transfer capability treatment in ISO’s proposed Zonal
Source Demand Curves – Reliability impacts of ISO’s proposed demand curves
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Agenda For Today
• December 28 FERC Order – Requires ISO to file sloped zonal demand curves by March 31, 2016
• Key Reliability Elements of ISO’s Proposal
• Local Sourcing approach – Zonal transfer capability assumptions for import-constrained zonal
demand curves
• Quantitative Reliability Impacts and Modeling for Proposed Demand Curves
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Additional Materials Available
• Markets Committee materials – October 2015
• Overview of ISO’s revised approach – November 2015
• Details of ISO’s method; assumptions and computed demand curves for FCA 10 zones; process and timing for annual updates
– December 2015 • ISO’s results for other zonal possibilities (e.g., FCA10 zones with an added
export zone); initial results for alternate, stakeholder approaches – January 2016
• Local sourcing approach; robustness; new results on price volatility; removal of administrative pricing rules
• Indicative curve data and spreadsheets
• ISO technical memo on FCM Demand Curve Methodology (Dec 7, 2015)
http://www.iso-ne.com/static-assets/documents/2015/12/a09_iso_memo_12_07_15.pdf
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DECEMBER 28 FERC ORDER Requires ISO to file sloped zonal demand curves by March 31, 2016
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December 28 FERC Order
• FERC Order requires “ISO-NE to submit Tariff revisions by March 31, 2016 providing for zonal sloped demand curves to be implemented beginning in FCA 11”
• Previous project schedule had the ISO filing shortly after the April PC
• To adhere to the Order, the schedule needs to be modified to meet the March 31st deadline set by FERC
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Updated Committee Schedule (1 of 3)
Jan. 2016 Discussion of reliability outcomes and zonal capacity transfer capability assumptions under ISO proposal
Feb. 2016 Continued discussion; Tariff language
March 2016 Reliability Committee vote
Tentative 2016 RC Schedule
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Potential Project Schedule 2016 (2 of 3)
Jan. 2016 Administrative pricing rules; further quantitative and qualitative results for ISO’s and stakeholders’ proposals
Feb. 2016 Continued discussion and results; Tariff language; potential amendments raised
March 2016 Continued discussion and results; final Tariff language (ISO proposal and amendments); Markets Committee vote
Tentative 2016 MC Schedule
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Potential Project Schedule (3 of 3)
Late March 2016 PC vote (additional meeting)
March 31 FERC filing. Tent. effective date June 2016. Implementation February 2017
Tentative Filing Schedule
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What Principles Should the FCM’s Sloped Demand Curves Aim to Satisfy?
1. Reliability. Meet the ISO’s reliability planning obligations
– System LOLE of 0.1 or less, on average (over the long-term) – An objective in previous design efforts
2. Sustainability. Over the long-term, the FCA’s average clearing price should be sufficient to attract entry when needed – Competitive new suppliers recover their fixed entry costs (Net CONE) – Both in the system and import-constrained zones – An objective in previous design efforts
3. Cost-Effectiveness. Procure capacity in zones cost-effectively
– Zonal curves should allocate capacity purchases among zones, given bid prices, to meet the system’s reliability requirements at least-cost
– Ensuring this objective is satisfied is more complex with zonal demand curves than in the system demand curve design
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Capacity Market’s Reliability Foundation
• To satisfy these principles, demand curves seek to balance capacity and reliability
• Capacity helps avoid ‘lost load’
• The sloped demand curves should be based, in part, on the marginal reliability impact of procuring additional capacity – Prices should be commensurate to the reliability benefit of
incremental capacity
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Resource Adequacy Indices
• Indices express the expected frequency, expected duration and/or expected magnitude of possible capacity deficiency (loss of load)
• LOLE (Loss of Load Expectation) – Expected number of days per year of loss of load [days/yr] – Commonly used metric of 1 day in 10 years
• LOLH (Loss of Load Hours) – Expected number of hours per year of loss of load [hrs/yr]
• EENS (Expected Energy Not Served) – Expected amount of unserved load [MWh/yr] – Also known as EUE (Expected Unserved Energy) or LOEE (Loss of
Energy Expectation)
A reference for further reading can be found at: http://www.nerc.com/files/2012_ProbA.pdf
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Marginal Reliability Impact of Capacity
• ISO’s planning models can calculate expected energy not served (EENS) as a measure of the expected ‘lost load’ – Calculated on a MWh per year basis – EENS depends on capacity in system overall, and in each capacity zone
• Marginal reliability impact (MRI) is the decrease in EENS (expected ‘lost load’) with another 1 MW of capacity – Differs for system and each zone
• Methodology calculates the MRI at the system and zonal level for range of capacity values – May be greater in import-constrained zones where capacity can serve
system or zone
• MRI (after sign change) declines smoothly with capacity, as shown to the right
• ISO’s planning models can calculate this function
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Demand Curves Based on the Marginal Reliability Impact are (Slightly) Convex
• When the system is short, deficiencies can occur more frequently, so an additional MW of capacity significantly reduces EENS because – At low MW quantities, MRI value is high – As capacity is added, the MRI decreases quickly meaning the slope is
relatively steep
• When the system is long, deficiencies are infrequent, so an additional MW of capacity has a small impact on EENS because – At high MW quantities, MRI value is low and relatively flat
• Consistent with these properties, demand curves will be based on the MRI function are downward sloping and convex
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• The methodology captures the difference in relative impact of additional capacity in different zones – Especially when the transfer
levels are close to or at the transfer capabilities
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Relative Impact
Rest-of-Pool
Import Constrained
Zone
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Local Sourcing Demand Curve Approach
• ISO’s modeling assumption builds on the current methodology used to generate the Local Sourcing Requirement based on both the TSA and LRA values – “For each import-constrained Capacity Zone, the Local Sourcing Requirement shall be
the amount needed to satisfy the higher of: (i) the Local Resource Adequacy Requirement as determined pursuant to Section III.12.2.1.1; or (ii) the Transmission Security Analysis Requirement as determined pursuant to Section III.12.2.1.2.”
• MRI calculations will use a capacity transfer capability of:
(N-1 limit) – max(TSA-LRA,0)
– Starts with N-1 limit, but includes adjustment based on the positive difference difference between TSA and LRA
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Example: SENE Capacity Transfer Capability
FCA 10 Input Parameters:
• N-1-1 Import Limit = 4,600 MW
• N-1 Import Limit = 5,700 MW
• Local Resource Adequacy (LRA) = 9,584 MW
• Transmission Security Adequacy (TSA) = 10,028 MW
Revised capacity transfer capability assumption for SENE zonal MRI calculations is:
5,700 MW – max(10,028 TSA - 9,584 LRA, 0) = 5,256 MW
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Indicative FCA-9 Curve Assumptions
• Net ICR = 34,189
• CT LSR = 7,331 (TSA)
• NEMA LSR = 3,572 (TSA)
• SEMA LSR = 7,479 (LRA)
• For more information see http://www.iso-ne.com/static-assets/documents/2014/08/2018-19_fca_icr_values_pspc_08282014.pdf
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DERIVING CURVES FOR EXPORT-CONSTRAINED ZONES Same methodology as that used in import-constrained zones produces congestion-based demand curves in export-constrained zones
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Export-Constrained Zones Derived Using Same Methodology As Import-Constrained Zones
• Curves in all constrained zones are based on the marginal reliability impact of shifting a MW of capacity from the rest-of-system zone into the zone
• Shift of capacity into import-constrained zones improves system reliability (reduces EENS) – Resulting curve in import-constrained zone therefore pays a positive
congestion price to capacity in the zone
• Shift of capacity into export-constrained zone decreases system reliability (increases EENS) – Resulting curve in export-constrained zones must therefore pay a
negative congestion price to capacity in the zone
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Export-Constrained MRI Curve is Downward Sloping and Negative
• MRI function is zero for low MW quantities as capacity in export-constrained zone provides equal reliability value to that in rest-of-system
• At higher MW quantities, MRI function slopes downward because marginal reliability impact of capacity in the zone decreases
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Notes: Indicative MCL = 8,830 MW for NNE in FCA 10. * November 16, 2015 Planning Advisory Committee: http://www.iso-ne.com/static-assets/documents/2015/11/a2_fcm_zonal_development_3_review_of_determinations_for_fca_10.pdf
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Probabilistic Reliability Calculations under Proposed Demand Curve
• Calculations for system-wide ICR, MCL for export-constrained zones, and LRA for import-constrained capacity zones remain unchanged – Same simulation model (GE MARS) – Same calculation methodology – Same stakeholder review process for input assumptions
• Deriving Demand Curves requires a series of MARS simulations to calculate the system-wide expected energy not served (EENS) – System curve based on the same ICR case – Zonal curve based on the same LRA/MCL case
• With adjusted N-1 limit for import-constrained zones
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EENS Calculations using MARS
• MARS is a sequential Monte Carlo simulation reliability model that can calculate the standard indices of – Daily LOLE (days/year)
• Currently used for calculating ICR and related values – Hourly LOLE (hours/year) – Expected Unserved Energy (LOEE in MWh/year)
• Same as EENS
&CNV-CRIT-00 CNC * CONVERGENCE-CRITERIA *---------------------------------------------------------------------------------------------------- AREA OR POOL TO DETERMINE HOUR OF DAILY PEAK (.IPKARP.) AAAAAAAA : "ALL ”
CALCULATED INDICES FOR 2019 ********** INTERCONNECTED *********** LOLE LOLE LOEE AREA OR POOL (days/yr) (hrs/yr) (MWh/yr) ------------------ --------- -------- ---------- BHE 0.00744 0.03100 0.130 ME 0.00000 0.00000 0.000 … NEPOOL 0.06558 0.35394 346.016
Sample output file
To have MARS calculate all three indices
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Quantitative Reliability Results on Indicative System Demand Curve
• Indicative System Demand Curve from Dec 2015 MC presentation (Using FCA 10 Inputs) • LOLE calculated assuming unconstrained system
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Quantitative Reliability Results on Indicative SENE Demand Curve
Indicative SENE Demand Curve from Jan 2016 MC presentation (Using FCA 10 Inputs)
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Quantitative Reliability Results on Indicative NNE Demand Curve
Indicative NNE Demand Curve from Dec 2015 MC presentation (Using FCA 10 Inputs)
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Resource Adequacy Evaluation of Modeled Outcomes under ISO Proposed Demand Curves (FCA10 Inputs)
• NPCC Resource Adequacy Design Criterion applied – System-wide LOLE <= 0.1 days/year
• Adequate if resources more than ICR
– N-1 limits used to reflect transmission limitation • Adequate if resources more than LRA in import-constrained zones • Deliverable if resources less than MCL in export-constrained zones
• Modeled outcomes based on Jan 2016 MC presentation using FCA10 inputs
SENE: LRA=9584 MW NNE: MCL=8830 MW System: ICR=34151 MW Supply Model MW Procured
Adequacy Evaluation MW Procured
Reliability Evaluation MW Procured
Reliability Evaluation
Model 1 10840 √ 8440 √ 34151 0
Model 2a 10840 √ 8440 √ 34712 561
Model 2b 10840 √ 8440 √ 34314 163
Model 2c 10840 √ 8440 √ 34012 -139
Model 2d 9950 √ 8440 √ 34151 0
Model 3 11069 (σ =468) √(on avg.) 8805 (σ =218) √(on avg.) 34554 (σ =255) 403 (on avg.)
Model 4a 10840 √ 8440 √ 34151 0
Model 4b 10840 √ 8440 √ 34151 0
Model 5a 9816 √ 8440 √ 34389 238
Model 6a 10807 (σ =164) √(on avg.) N/A N/A 34127 (σ =75) -24 (on avg.)
Model 6b 10809 (σ =151) √(on avg.) N/A N/A 34113 (σ =119) -38 (on avg.)